code: def forward(self, x):
      x = F.relu(self.conv1(x))
      x = F.max_pool2d(x, 2, 2)
      x = F.relu(self.conv2(x))
      x = F.max_pool2d(x, 2, 2)
      x = x.view(-1, 4 * 4 * 50)
      x = F.relu(self.fc1(x))
      x = self.fc2(x)
      return F.log_softmax(x, dim=1)
  
file_path: analytics-zoo/pyzoo/zoo/examples/pytorch/train/mnist/main.py
imports: from __future__ import print_function
  import argparse
  import torch
  import torch.nn
  import torch.nn.functional
  from torchvision import datasets, transforms
  from zoo.pipeline.api.torch import TorchModel, TorchLoss, TorchOptim
  from zoo.pipeline.estimator import *
  from bigdl.optim.optimizer import SGD, Adam
  from zoo.common.nncontext import *
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.metrics import Accuracy
  from zoo.util.utils import detect_conda_env_name
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: F